Capacity of Two-Way Linear Deterministic Diamond Channel
|
|
- Camilla Barton
- 6 years ago
- Views:
Transcription
1 Capacity of Two-Way Linear Deterministic Diamond Channel Mehdi Ashraphijuo Columbia University Vaneet Aggarwal Purdue University Xiaodong Wang Columbia University Abstract In this paper, we study the capacity regions of two-way linear deterministic diamond channels. We show that the capacity of the diamond channel in each direction can be simultaneously achieved for all values of channel parameters, where the forward and backward channel parameters are not necessarily the same. We propose a relay strategy called reverse amplify-and-forward strategy and show that this strategy and its variants combined with proper transmission strategies achieve the capacity of linear deterministic diamond channel. I. INTRODUCTION Two-way communication between two nodes was first studied by Shannon [1]. There have been many attempts recently to demonstrate two-way communications experimentally [2, 3]. The two-way relay channel where two nodes communicate to each other in the presence of a single relay, has been widely studied [4, 5]. In this paper, we will consider the two-way diamond channel, where two nodes communicate to each other in the presence of two relays. Also, [6, 7] consider different kinds of collaboration between the nodes. The diamond channel was first introduced in [8], and consists of one transmitter, two relays and a receiver. The twoway half-duplex K-relay channel has been studied using the amplify-and-forward strategy at the relays [9, 10]. The design of relay beamformers based on minimizing the transmit power subject to the received signal-to-noise ratio constraints was considered in [10]. Furthermore, achievability schemes using time-sharing are investigated in [11] for a symmetric reciprocal diamond channel with half-duplex nodes and the inner and outer bounds are compared using simulations. However, we show that the achievability scheme in [11] has an unbounded gap from the capacity. None of the prior works gave a capacity achieving strategy for a two-way full-duplex diamond channel. In this paper, we consider a linear deterministic model which was proposed in [12], and has been shown to lead to approximate capacity results for Gaussian channels in [5, 13, 14]. We study the capacity region of a two-way linear deterministic diamond channel where the forward and backward channel gains are not necessarily the same. We find that the capacity in each direction can be simultaneously achieved. Thus, each user can transmit at a rate which is not affected by the fact that the relays receive the superposition of the signals. In order to achieve the capacity in each direction separately, we develop new transmission strategies by the transmitters and the relays. The strategies proposed for the one-way diamond channel in [12] do not directly work for two-way channels. The reason is that they are dependent on the channel parameters in the forward direction; but for two-way channels we need a strategy that is optimal for both directions. For the special case when the diamond channel reduces to a two-way relay channel (channel gains to and from one of the relays are zeros), our proposed strategy reduces to a reverse amplifyand-forward strategy, where the relay reverses the order of the received signals to form the transmitted signal. The proposed strategy in this case is different from the one in [5] for twoway relay channels, since the relay strategy in [5] depends on the channel parameters, while ours simply reverses the order of the input. On the other hand, the transmission strategy at the source nodes in our approach is dependent on the channel parameters unlike that in [5]. Thus, the proposed strategy in this paper makes the relay strategy simpler by compensating in the transmission strategy at the source nodes. For a general two-way diamond channel, we give different strategies based on the parameters of both the forward and backward channels. Depending on the forward and backward channel gains we consider four cases; these cases are further subdivided. Two special cases are Cases and Our first main result is that if neither the forward, nor the backward channel is of one of these two cases, then the proposed reverse amplify-and-forward strategy at the relays is optimal. We next consider the case that exactly one of the forward and backward channels is of Case or Without loss of generality, we assume that the forward channel is of one of the two mentioned cases. For each of these two cases, we give four new strategies at the relay which involve various modifications to the reverse amplify-and-forward strategy, such as repeating some of the streams on multiple levels or changing the order of transmission at some levels at one of the relays. Furthermore, the transmission strategy for the forward direction is rather straightforward by simply sending capacity number of bits at the lowest levels. We show that all these modified strategies achieve the capacity in the forward direction. The choice of the strategies then depends on the parameters in the backward direction. We show that for each case of the backward channel, at least one of the four proposed strategies achieves the capacity for the backward direction. Finally, the case when both the forward and backward channels are of Case or is considered. Here, a modified form of the relay strategies proposed above is used to achieve the capacity in both directions /15/$ IEEE 1896 ISIT 2015
2 II. CHANNEL MODEL The linear deterministic channel model was proposed in [12] to focus on signal interactions instead of the additive noise, and to obtain insights for the Gaussian channel. A two-way diamond channel consists of two nodes (denoted by A and B) who wish to communicate to each other through two relays (denoted by R 1 and R 2 ). We use non-negative integers n Ak, n Bk, n ka, and n kb, to represent the channel gains from node A to R k, node B to R k, R k to node A, and R k to node B, respectively, for k {1, 2}. In this paper, the links in the direction from A to B are said to be in the forward direction and those from B to A are in the backward direction. Let us define q AR max k {n Ak }, q RB max k {n kb }, q BR max k {n Bk }, q RA max k {n ka }, qk I max{n Ak, n Bk }, and qk O max{n ka, n kb } for k {1, 2}. Furthermore, denote the channel input at transmitter u, for u {A, B}, at time i as X u,i = F 2 q ur, such that X 1 u,i and XquR u,i [X qur u,i,, X2 u,i, X1 u,i ]T represent the least and the most significant bits of the transmitted signal, respectively. Also, we define Xuk,i R = [X qur u,i,, XquR nuk+2 u,i, X qur nuk+1 u,i, 0,..., 0 }{{} ]T, for k qk I nuk {1, 2}. At each time i, the received signal at R k is given by Y k,i = D qi k nak q I k XAk,i R + D qi k nbk X R qk I Bk,i mod 2, (1) where D q I k is a qk I qi k shift matrix as Eq. (9) in [12]. Also if we have Y k,i = [Y qi k k,i,, Y k,i 2, Y k,i 1 ]T, define V k,i = [0,, 0, Y min(qi k,qo k ) k,i,, Yk,i 2, Y k,i 1 ]T, for k {1, 2}, where the first (qk O qi k )+ elements of V k,i are zero. Furthermore, define T k,i f k,i (V k,1,..., V k,i 1 ) where ( ) i 1 f k,i : R qo k R q O k is a function at Rk which converts V k,1,..., V k,i 1 to the output signal at time i. We represent [ ] T T k,i s elements as T k,i = Tk,i 1, T k,i 2,, T qo k k,i. Also, we define T ku,i = [T k,i 1, T k,i 2,, T nku k,i, 0,..., 0 ] }{{} T for u {A, B}. q Ru n ku At each time i, the received signal at the receivers u {A, B} is given by 2 Y u,i = Dq qru nku Ru T ku,i mod 2. (2) k=1 Source u picks a message W u that it wishes to communicate to ū (u, ū {A, B}, u ū), and transmits signal at each time i which is a function of W u and Yu i 1 = {Y u,i 1, Y u,i 2,..., Y u,1 }. Each destination ū uses a decoder, which is a mapping gū : R m Wū {1,..., W u } from the m received signals and the message at the receiver to the source message indices ( W u is the number of messages of node u that can be chosen). We say that the rate pair log WA (R A m, R log WB B m ) is achievable if the probability of error in decoding both messages by their corresponding destinations can be made arbitrarily close to 0 as m. The capacity region is the convex hull of all the achievable rate pairs (R A, R B ). III. CAPACITY OF TWO-WAY LINEAR DETERMINISTIC DIAMOND CHANNEL In this section, we state the main result that the cut-set bound for the diamond channel in each direction can be simultaneously achieved, thus giving the capacity region for the two-way linear deterministic diamond channel. It can be seen that max{n A1, n A2 } and max{n 1B, n 2B } are cut-set bounds on the transmissions from A and to B, respectively. Moreover, n A1 + n 2B and n A2 + n 1B are cut-set bounds on the sum of the two paths for the transmission from A to B. The same observation can be made for the other direction. Theorem 1. For the two-way linear deterministic diamond channel, the capacity region is given as follows: R A C AB min{max{n A1, n A2 }, max{n 1B, n 2B }, n A1 + n 2B, n A2 + n 1B }, (3) R B C BA min{max{n B1, n B2 }, max{n 1A, n 2A }, n B1 + n 2A, n B2 + n 1A }. (4) We note that the outer-bound is the cut-set bound, and thus the proof is straightforward. We will prove the achievability of the rate pair (C AB, C BA ). We consider four main cases and several subcases depending on the forward channel parameters as follows. Case 1: C AB = n A2 + n 1B. Case 2: C AB = n A1 + n 2B. Case 3: C AB = max{n A1, n A2 }. We call it Type 1, if max{n A1, n A2 } = n A1, and Type 2 otherwise. For Type i, where i, j {1, 2}, i j, we have: Case 3.1: n ib < C AB. We divide it into two sub-cases: Case 3.1.1: n jb n Aj + n ib. Case 3.1.2: n jb < n Aj + n ib. Case 3.2: n ib C AB. Case 4: C AB = max{n 1B, n 2B } We call it Type 1, if max{n 1B, n 2B } = n 1B, and Type 2 otherwise. For Type i, where i, j {1, 2}, i j, we have: Case 4.1: n Ai < C AB. We divide it into two sub-cases: Case 4.1.1: n Aj n jb + n Ai. Case 4.1.2: n Aj < n jb + n Ai. Case 4.2: n Ai C AB. Similarly we divide the backward channel into four main cases and several subcases where the case definition is obtained by interchanging A and B in the forward direction cases. For instance, Case 1 in the backward direction is C BA = n B2 + n 1A. We divide the proof into three parts, depending on the cases in which forward and backward channel gain parameters lie. The first part is when neither the forward channel nor the backward channel is of Case or (Section III-A). The second part is when exactly one of the forward and backward channels is of Case or (Section III-B). And finally the third part is when both the forward and backward channels are of Case or (Section III-C). 1897
3 A. Neither the forward channel nor backward channel is of Case or In this scenario, we use a reverse amplify-and-forward strategy in the relays to achieve the rate pair (C AB, C BA ). Assume a particular relay (say R i ) gets n Ai levels from node A and n Bi levels from node B and transmits qi O levels. It receives Y A1 = [a nai,..., a 1 ] T from node A and Y B1 = [b nbi,..., b 1 ] T from node B. Then it sends out the following signal to nodes A and B X Ri = a 1. a min(nai,q O i ) 0 (q O i n Ai) + + b 1. b min(nbi,q O i ) 0 (q O i n Bi) + mod 2. (5) We call this relay strategy as Relay Strategy 0 (also called reverse amplify-and-forward ). We will keep the strategy at the relays the same, and for different cases use different strategies for transmission at nodes A and B. Since we need to show that the rate pair (C AB, C BA ) is achievable, it is enough to show that there is a transmission strategy for node A such that with the above relay strategy, node B is able to decode the data in a one-way diamond channel because any interference by node B on the received signal can be canceled by node B which knows the interfering signal (Showing it for one direction is enough since the same arguments hold for the other). Thus, we only consider one-way diamond channel for this case. We further consider the case when n A1, n A2, n 1B, n 2B > 0 since otherwise the diamond channel reduces to a relay channel or no connection between the nodes A and B, and in both cases it is easy to see that node A sending C AB bits on the lowest levels achieves this rate in the forward direction. It has been shown in Appendix 1 of [15] that there is a transmission strategy for each of the cases (except for Case or 4.1.2) such that the above relay strategy achieves the capacity for one-way diamond channel. B. Exactly one of the forward and backward channels is of Case or We assume that the forward channel is of Case or without loss of generality. The other case where the backward channel is of Case or can be proven symmetrically. Since we need to show that the rate pair (C AB, C BA ) is achievable, we will describe a few relay strategies for which the same transmission strategy is used at node A such that node B is able to decode the corresponding message. Furthermore, we will show that at least one of these strategies is optimal for the backward channel for each case of the backward channel parameters. As before we consider the case when n A1, n A2, n 1B, n 2B > 0. In the remainder of this section, we assume that the forward channel is of Case The case that the forward channel is of Case is treated in Appendix 2 of [15]. When the forward channel is of Case 3.1.2, node A transmits [a CAB,..., a 1 ] T. Also, the transmission strategy for node B depends on the channel gains in the backward direction. For the relay strategy, we will choose one of the four strategies explained in the following depending on the backward channel parameters. We prove that all of these strategies are optimal for the forward channel for any set of parameters. The parameters associated with each relay strategy proposed here are only based on the forward channel gains, and we will show that at least one of the proposed strategies is optimal for each choice of the backward channel parameters. Note that using Relay Strategy 0 in both relays, node B cannot necessarily decode the message if the forward channel is of Case or 4.1.2, when the above transmission strategy is used by node A. Remark 1. All relay strategies in this subsection are defined with respect to the forward channel parameters (and in favor of the forward channel direction 1 ) because we assumed that the forward channel is either of Case or and the backward channel is not of these cases. We note that Relay Strategy 0 is symmetric and is not dependent on the channel gains in any direction. In Section III-C, we will generalize some of these strategies to be based on the parameters of both the forward and backward channels. 1) Relay Strategy 1:: If the forward channel is of Case Strategy 1 is used at R ī, where i, ī {1, 2}, i ī. Here, we define Relay Strategy 1 at R 2 (forward channel of Case roles of relays R 1 and R 2 (interchanging 1 and 2 and forward channel of Case Type 2). As shown in Figure 1, if R 2 receives a block of n 2B bits, first it will reverse them as in Relay Strategy 0 and then changes the order of the first n 1B (n A1 n A2 ) streams 2 with the next n A1 n 1B streams. Node A transmits [a CAB,..., a 1 ] T. The received signals can Fig. 1. Relay Strategy 1 at R 2. be seen in Figure 2. We use (R i, B j ) to denote block number j from R i. Bits that are not delivered to node B from R 1 using Relay Strategy 0, (a n1b+1,..., a na1 ), are all sent at the highest levels from R 2 to node B and thus are decoded with no interference (block (R 2, B 1 )). The remaining bits can be decoded by starting from the lowest level of reception in B (a n1b in block (R 1, B 4 )) and removing the effect of the decoded bits and going up. 1 In the sense that the strategies are designed so that the forward communication achieves the capacity. 2 In the following relay strategies, we divide the streams into multiple substreams. The number of streams in each sub-stream is a non-negative number when the forward channel is of Case Type
4 levels Contribution from relay Contribution from relay Fig. 2. by using Relay Strategy 1 when the forward channel is of Case Type 1. 2) Relay Strategy 2:: If the forward channel is of Case Strategy 2 is used at R ī, where i, ī {1, 2}, i ī. Here, we define Relay Strategy 2 at R 2 (forward channel of Case roles of R 1 and R 2 (interchanging 1 and 2 and forward channel of Case Type 2). It is similar to Relay Strategy 0 with the only difference that R 2 repeats a part of the top n A2 streams after reverse-amplify-and-forward, as explained below in nine separate scenarios based on the parameters of the forward channel. We note that the repetition of streams is based on the received signal at the relay. However, we describe only the forward direction to show that the messages can be decoded. We partition the four-dimensional space (n A1, n A2, n 1B, n 2B ) into multiple parts, and we consider one of the case below. The proof for the rest of cases is given in Section IV of [15]. This case corresponds to {n 2B + (n A1 n A2 ) n A2 + n 1B, n 1B (n A1 n A2 ) + (n 2B n 1B )}. Figure 3 depicts the received signal at node B (ignoring the effect of transmitted signal from B) assuming that both relays use Relay Strategy 0. The repetitions will be described below to show that messages can be decoded with the proposed strategies. R 2 repeats the Contribution from relay Contribution from relay Block No Block No from the other relay. Then, subtract the corresponding signals (blocks (R 1, B 3 ) and (R 1, B 4 )). Furthermore, block (R 2, B 4 ) can be decoded from repetitions because their interference is already decoded. Then, subtract the corresponding signals (block (R 2, B 2 )). Consequently, block (R 1, B 2 ) are decoded because their interference (block (R 2, B 2 )) was decoded earlier. Finally, block (R 2, B 3 ) can be decoded because all its interference signals have been decoded. 3) Relay Strategy 3:: If the forward channel is of Case Strategy 3 is used at R ī, where i, ī {1, 2}, i ī. Here, we define Relay Strategy 3 at R 2 (forward channel of Case roles of relays R 1 and R 2 (interchanging 1 and 2 and forward channel of Case Type 2). As shown in Figure 4, if R 2 receives a block of n 2B bits, first it will reverse them as in Relay Strategy 0 and then changes the order of the n A2 (n 2B n 1B ) streams right after the first n 2B n 1B streams, with the following n 2B n A2 streams. Node A Fig. 4. Relay Strategy 3 at R 2. transmits [a CAB,..., a 1 ] T, and it can be shown to be decoded at node B. 4) Relay Strategy 4:: If the forward channel is of Case Type i, then Relay Strategy 0 is used at R ī, where i, ī {1, 2}, i ī, and Relay Strategy 4 is used at R i. Here, we define Relay Strategy 4 at R 1 (forward channel of Case Type 1), while that for R 2 can be obtained by interchanging roles of R 1 and R 2 (interchanging 1 and 2 and forward channel of Case Type 2). As shown in Figure 5, if R 1 receives a block of n 1B bits, first it will reverse them as in Relay Strategy 0 and then changes the order of the first n A1 n A2 streams with the next n 1B (n A1 n A2 ) streams. Node A Fig. 3. The received signals at node B (ignoring the effect of transmitted signal from B) assuming that both relays use Relay Strategy 0 for channel parameters of case {n 2B + (n A1 n A2 ) n A2 + n 1B, n 1B (n A1 n A2 ) + (n 2B n 1B )}. streams in block (R 2, B 2 ) on block (R 2, B 4 ). Using this strategy, block (R 2, B 1 ) will be decoded from the top levels of the received signal from R 2 since there is no interference Fig. 5. Relay Strategy 4 at R 1. transmits [a CAB,..., a 1 ] T. Bits that are not delivered to node B from R 2 using Relay Strategy 0 in the block (R 1, B 4 ) are decoded without any interference. The remaining bits can be decoded by starting from the highest level (a na1 n A2+1 in block (R 2, B 1 )) and removing the effect of the decoded bits. 1899
5 These strategies can be used at different relays to achieve the optimal rate. For instance, if the backward channel is of Case 1 and the forward channel is of Case Type 1, the following strategy is used. If n A2 > n B2, we use Relay Strategy 2 at R 2 and Relay Strategy 0 at R 1. Otherwise use Relay Strategy 1 at R 2 and Relay Strategy 0 at R 1. If n A2 > n B2, R 2 repeats from the streams that are already decoded from the highest levels received in A, on the lower levels, and otherwise it just changes the order of some of the equations at the highest levels received in A, which does not affect the decoding. Four new relay strategies are needed for Case 4.1.2, whose details can be seen in [15]. C. Both the forward and backward channels are either of Case or In Section III-B, we used Relay Strategy 2 or Relay Strategy 6 as one of the achievability strategies when the forward channel is of Case or 4.1.2, respectively. In this section, we show that using a modified combination of these strategies achieve the optimal capacity region when both the forward and backward channels are either of Case or We will define Relay Strategy (m i, n i ) at R i for i {1, 2}, m i, n i {0, 2, 6}. If the forward channel is of Case 3.1.2, at R 1, we use m 1 = 0 when the forward channel is Type 1 and m 1 = 2 otherwise. At R 2, we use m 2 = 2 when the forward channel is Type 1 and m 2 = 0 otherwise. If the forward channel is of Case 4.1.2, at R 1, we use m 1 = 6 when the forward channel is Type 1 and m 1 = 0 otherwise. At R 2, we use m 2 = 0 when the forward channel is Type 1 and m 2 = 6 otherwise. The value of n i is determined the same way based on the backward channel parameters. Relay Strategy (m i, 0) at R i uses Relay Strategy m i at R i based on the forward channel parameters, and Relay Strategy (0, n i ) at R i uses Relay Strategy n i based on the backward channel parameters. For the remaining strategies (m i, n i ) {(2, 2), (2, 6), (6, 2), (6, 6)} at R i, we use the combination of the repetitions suggested by Relay Strategies m i based on the forward channel parameters, and n i based on the backward channel parameters. If these two repetitions happen at the same level, we sum these modulo 2. However, there are some modifications to account for repetitions adding to zero modulo 2, or multiple repetitions due to different strategies at the relays. The modifications are as follows. 1) If the repetitions happen in the same relay, i.e., m 1 = n 1 = 0 or m 2 = n 2 = 0: In case the repetition of a particular signal by both the forward and backward strategies is suggested at the same level, we send the repeated signal. If different repeated signals are suggested at a particular level, we send the sum of these two signals modulo two. 2) If the repetitions happen in different relays, i.e., m 1 = n 2 = 0 or m 2 = n 1 = 0, we consider two cases. In case that the repetitions of some streams from two relays are from the same level and are repeated on the same level at node B (ignoring the backward signal component) R i skips repetitions at the corresponding levels if the forward channel is of Case Type i and R ī skips repetitions at the corresponding levels if the forward channel is of Case Type i. In case that the repetitions of some streams from two relays are from the same level and are repeated on the same level at node A (ignoring the forward signal component) R i skips repetitions at the corresponding levels if the backward channel is of Case Type i and R ī skips repetitions at the corresponding levels if the backward channel is of Case Type i. We use the same transmission strategy as in Section III-B for channel of both Cases and 4.1.2, and the decoding of the messages at the receivers can be shown. Detailed proofs can be seen in [15]. IV. CONCLUSIONS In this paper, we studied the capacity of the bidirectional (or two-way) diamond channel with two nodes and two relays. We used the deterministic approach to capture the essence of the problem and to determine capacity-achieving transmission and relay strategies. Depending on the forward and backward channel gains, we used either a reverse amplify-and-forward or a particular modified strategy involving repetitions, and reversing order of some streams at the relays. REFERENCES [1] C. Shannon, Two-way communication channels, in Proc. 4th Berkeley Symp. Mathematical Statistics Probability, 1961, pp [2] S. Chen, M. Beach, and J. McGeehan, Division-free duplex for wireless applications, Electronics Letters, vol. 34, no. 2, pp , Jan [3] A. K. Khandani, Methods for spatial multiplexing of wireless twoway channels, US patent, filed Oct (provisional patent filed Oct. 2005), issued Oct [4] B. Rankov and A. Wittneben, Achievable rate regions for the two-way relay channel, in Proc. IEEE Int. Symp. Inform. Theory (ISIT), Jul. 2006, pp [5] A. Avestimehr, A. Sezgin, and D. Tse, Capacity of the two-way relay channel within a constant gap, European Transactions on Telecommunications, vol. 21, no. 4, pp , Jun [6] M. Ashraphijuo, V. Aggarwal, and X. Wang, On the capacity region and the generalized degrees of freedom region for MIMO interference channel with feedback, IEEE Trans. Inform. Theory, vol. 59, no. 12, pp , Dec [7], On the capacity and degrees of freedom regions of two-user MIMO interference channels with limited receiver cooperation, IEEE Trans. Inform. Theory, vol. 60, no. 7, pp , Jul [8] B. Schein, Distributed coordination in network information theory, Ph.D. Dissertation, Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, [9] R. Vaze and R. W. Heath, On the capacity and diversity-multiplexing tradeoff of the two-way relay channel, IEEE Trans. Inform. Theory, vol. 57, no. 7, pp , Jul [10] T. Mirfakhraie, Optimal three-time slot distributed beamforming for two-way relaying, M.Sc. Dissertation, Ontario Institute of Technology, Dept. of Electrical and Computer Engineering, [11] A. T. P. V, S. Bhashyam, The gaussian two-way diamond channel, in Annual Allerton Conference on Communication, Control, and Computing, Oct [12] A. Avestimehr, S. Diggavi, and D. Tse, Wireless network information flow: A deterministic approach, IEEE Trans. Inform. Theory, vol. 57, no. 4, pp , Apr [13] M. Ashraphijuo, V. Aggarwal, and X. Wang, On the symmetric K-user interference channels with limited feedback, Submitted to IEEE Trans. Inform. Theory, arxiv: , Mar [14] A. Vahid, C. Suh, and A. Avestimehr, Interference channels with ratelimited feedback, IEEE Trans. Inform. Theory, vol. 58, no. 5, pp , May [15] M. Ashraphijuo, V. Aggarwal, and X. Wang, On the capacity regions of two-way diamond channels, Submitted to IEEE Trans. on Inf. Theory, ArXiv: , Oct
On the Capacity Regions of Two-Way Diamond. Channels
On the Capacity Regions of Two-Way Diamond 1 Channels Mehdi Ashraphijuo, Vaneet Aggarwal and Xiaodong Wang arxiv:1410.5085v1 [cs.it] 19 Oct 2014 Abstract In this paper, we study the capacity regions of
More informationTWO-WAY communication between two nodes was first
6060 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 61, NO. 11, NOVEMBER 2015 On the Capacity Regions of Two-Way Diamond Channels Mehdi Ashraphijuo, Vaneet Aggarwal, Member, IEEE, and Xiaodong Wang, Fellow,
More informationHow (Information Theoretically) Optimal Are Distributed Decisions?
How (Information Theoretically) Optimal Are Distributed Decisions? Vaneet Aggarwal Department of Electrical Engineering, Princeton University, Princeton, NJ 08544. vaggarwa@princeton.edu Salman Avestimehr
More informationMulti-user Two-way Deterministic Modulo 2 Adder Channels When Adaptation Is Useless
Forty-Ninth Annual Allerton Conference Allerton House, UIUC, Illinois, USA September 28-30, 2011 Multi-user Two-way Deterministic Modulo 2 Adder Channels When Adaptation Is Useless Zhiyu Cheng, Natasha
More informationJoint Relaying and Network Coding in Wireless Networks
Joint Relaying and Network Coding in Wireless Networks Sachin Katti Ivana Marić Andrea Goldsmith Dina Katabi Muriel Médard MIT Stanford Stanford MIT MIT Abstract Relaying is a fundamental building block
More informationDegrees of Freedom of the MIMO X Channel
Degrees of Freedom of the MIMO X Channel Syed A. Jafar Electrical Engineering and Computer Science University of California Irvine Irvine California 9697 USA Email: syed@uci.edu Shlomo Shamai (Shitz) Department
More informationSymmetric Decentralized Interference Channels with Noisy Feedback
4 IEEE International Symposium on Information Theory Symmetric Decentralized Interference Channels with Noisy Feedback Samir M. Perlaza Ravi Tandon and H. Vincent Poor Institut National de Recherche en
More informationTwo Models for Noisy Feedback in MIMO Channels
Two Models for Noisy Feedback in MIMO Channels Vaneet Aggarwal Princeton University Princeton, NJ 08544 vaggarwa@princeton.edu Gajanana Krishna Stanford University Stanford, CA 94305 gkrishna@stanford.edu
More informationApproaching the Capacity of the Multi-Pair Bidirectional Relay Network via a Divide and Conquer Strategy
Approaching the Capacity of the Multi-Pair Bidirectional elay Network via a Divide and Conquer Strategy Salman Avestimehr Cornell In collaboration with: Amin Khajehnejad (Caltech), Aydin Sezgin (UC Irvine)
More informationState of the Cognitive Interference Channel
State of the Cognitive Interference Channel Stefano Rini, Ph.D. candidate, srini2@uic.edu Daniela Tuninetti, danielat@uic.edu Natasha Devroye, devroye@uic.edu Interference channel Tx 1 DM Cognitive interference
More informationFeedback via Message Passing in Interference Channels
Feedback via Message Passing in Interference Channels (Invited Paper) Vaneet Aggarwal Department of ELE, Princeton University, Princeton, NJ 08544. vaggarwa@princeton.edu Salman Avestimehr Department of
More informationDegrees of Freedom of Multi-hop MIMO Broadcast Networks with Delayed CSIT
Degrees of Freedom of Multi-hop MIMO Broadcast Networs with Delayed CSIT Zhao Wang, Ming Xiao, Chao Wang, and Miael Soglund arxiv:0.56v [cs.it] Oct 0 Abstract We study the sum degrees of freedom (DoF)
More informationRelay Scheduling and Interference Cancellation for Quantize-Map-and-Forward Cooperative Relaying
013 IEEE International Symposium on Information Theory Relay Scheduling and Interference Cancellation for Quantize-Map-and-Forward Cooperative Relaying M. Jorgovanovic, M. Weiner, D. Tse and B. Nikolić
More informationOn the Capacity of Multi-Hop Wireless Networks with Partial Network Knowledge
On the Capacity of Multi-Hop Wireless Networks with Partial Network Knowledge Alireza Vahid Cornell University Ithaca, NY, USA. av292@cornell.edu Vaneet Aggarwal Princeton University Princeton, NJ, USA.
More informationThe Z Channel. Nihar Jindal Department of Electrical Engineering Stanford University, Stanford, CA
The Z Channel Sriram Vishwanath Dept. of Elec. and Computer Engg. Univ. of Texas at Austin, Austin, TX E-mail : sriram@ece.utexas.edu Nihar Jindal Department of Electrical Engineering Stanford University,
More informationOn the Achievable Diversity-vs-Multiplexing Tradeoff in Cooperative Channels
On the Achievable Diversity-vs-Multiplexing Tradeoff in Cooperative Channels Kambiz Azarian, Hesham El Gamal, and Philip Schniter Dept of Electrical Engineering, The Ohio State University Columbus, OH
More informationWireless Network Coding with Local Network Views: Coded Layer Scheduling
Wireless Network Coding with Local Network Views: Coded Layer Scheduling Alireza Vahid, Vaneet Aggarwal, A. Salman Avestimehr, and Ashutosh Sabharwal arxiv:06.574v3 [cs.it] 4 Apr 07 Abstract One of the
More informationGeneralized Signal Alignment For MIMO Two-Way X Relay Channels
Generalized Signal Alignment For IO Two-Way X Relay Channels Kangqi Liu, eixia Tao, Zhengzheng Xiang and Xin Long Dept. of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China Emails:
More informationDEGRADED broadcast channels were first studied by
4296 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 54, NO 9, SEPTEMBER 2008 Optimal Transmission Strategy Explicit Capacity Region for Broadcast Z Channels Bike Xie, Student Member, IEEE, Miguel Griot,
More informationThe Multi-way Relay Channel
The Multi-way Relay Channel Deniz Gündüz, Aylin Yener, Andrea Goldsmith, H. Vincent Poor Department of Electrical Engineering, Stanford University, Stanford, CA Department of Electrical Engineering, Princeton
More informationInterference Mitigation Through Limited Transmitter Cooperation I-Hsiang Wang, Student Member, IEEE, and David N. C.
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 57, NO 5, MAY 2011 2941 Interference Mitigation Through Limited Transmitter Cooperation I-Hsiang Wang, Student Member, IEEE, David N C Tse, Fellow, IEEE Abstract
More informationSHANNON showed that feedback does not increase the capacity
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 57, NO. 5, MAY 2011 2667 Feedback Capacity of the Gaussian Interference Channel to Within 2 Bits Changho Suh, Student Member, IEEE, and David N. C. Tse, Fellow,
More informationOn Multi-Server Coded Caching in the Low Memory Regime
On Multi-Server Coded Caching in the ow Memory Regime Seyed Pooya Shariatpanahi, Babak Hossein Khalaj School of Computer Science, arxiv:80.07655v [cs.it] 0 Mar 08 Institute for Research in Fundamental
More informationDegrees of Freedom of Bursty Multiple Access Channels with a Relay
Fifty-third Annual Allerton Conference Allerton House, UIUC, Illinois, USA September 29 - October 2, 205 Degrees of Freedom of Bursty Multiple Access Channels with a Relay Sunghyun im and Changho Suh Department
More informationMULTIPATH fading could severely degrade the performance
1986 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 12, DECEMBER 2005 Rate-One Space Time Block Codes With Full Diversity Liang Xian and Huaping Liu, Member, IEEE Abstract Orthogonal space time block
More informationBlock Markov Encoding & Decoding
1 Block Markov Encoding & Decoding Deqiang Chen I. INTRODUCTION Various Markov encoding and decoding techniques are often proposed for specific channels, e.g., the multi-access channel (MAC) with feedback,
More informationOn Information Theoretic Interference Games With More Than Two Users
On Information Theoretic Interference Games With More Than Two Users Randall A. Berry and Suvarup Saha Dept. of EECS Northwestern University e-ma: rberry@eecs.northwestern.edu suvarups@u.northwestern.edu
More informationDoF Analysis in a Two-Layered Heterogeneous Wireless Interference Network
DoF Analysis in a Two-Layered Heterogeneous Wireless Interference Network Meghana Bande, Venugopal V. Veeravalli ECE Department and CSL University of Illinois at Urbana-Champaign Email: {mbande,vvv}@illinois.edu
More informationInterference: An Information Theoretic View
Interference: An Information Theoretic View David Tse Wireless Foundations U.C. Berkeley ISIT 2009 Tutorial June 28 Thanks: Changho Suh. Context Two central phenomena in wireless communications: Fading
More informationAnalog network coding in the high-snr regime
Analog network coding in the high-snr regime The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation As Published Publisher Médard,
More informationAligned Interference Neutralization and the Degrees of Freedom of the Interference Channel
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 58, NO 7, JULY 2012 4381 Aligned Interference Neutralization and the Degrees of Freedom of the 2 2 2 Interference Channel Tiangao Gou, Student Member, IEEE,
More informationInterference Management in Wireless Networks
Interference Management in Wireless Networks Aly El Gamal Department of Electrical and Computer Engineering Purdue University Venu Veeravalli Coordinated Science Lab Department of Electrical and Computer
More informationI. INTRODUCTION. Fig. 1. Gaussian many-to-one IC: K users all causing interference at receiver 0.
4566 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 56, NO. 9, SEPTEMBER 2010 The Approximate Capacity of the Many-to-One One-to-Many Gaussian Interference Channels Guy Bresler, Abhay Parekh, David N. C.
More informationWhen Network Coding and Dirty Paper Coding meet in a Cooperative Ad Hoc Network
When Network Coding and Dirty Paper Coding meet in a Cooperative Ad Hoc Network Nadia Fawaz, David Gesbert Mobile Communications Department, Eurecom Institute Sophia-Antipolis, France {fawaz, gesbert}@eurecom.fr
More informationMessage Passing in Distributed Wireless Networks
Message Passing in Distributed Wireless Networks Vaneet Aggarwal Department of Electrical Engineering, Princeton University, Princeton, NJ 08540. vaggarwa @princeton.edu Youjian Liu Department of ECEE,
More informationELEC E7210: Communication Theory. Lecture 11: MIMO Systems and Space-time Communications
ELEC E7210: Communication Theory Lecture 11: MIMO Systems and Space-time Communications Overview of the last lecture MIMO systems -parallel decomposition; - beamforming; - MIMO channel capacity MIMO Key
More informationThe Degrees of Freedom of Full-Duplex. Bi-directional Interference Networks with and without a MIMO Relay
The Degrees of Freedom of Full-Duplex 1 Bi-directional Interference Networks with and without a MIMO Relay Zhiyu Cheng, Natasha Devroye, Tang Liu University of Illinois at Chicago zcheng3, devroye, tliu44@uic.edu
More information5984 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 56, NO. 12, DECEMBER 2010
5984 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 56, NO. 12, DECEMBER 2010 Interference Channels With Correlated Receiver Side Information Nan Liu, Member, IEEE, Deniz Gündüz, Member, IEEE, Andrea J.
More informationInformation flow over wireless networks: a deterministic approach
Information flow over wireless networks: a deterministic approach alman Avestimehr In collaboration with uhas iggavi (EPFL) and avid Tse (UC Berkeley) Overview Point-to-point channel Information theory
More informationMinimum number of antennas and degrees of freedom of multiple-input multiple-output multi-user two-way relay X channels
IET Communications Research Article Minimum number of antennas and degrees of freedom of multiple-input multiple-output multi-user two-way relay X channels ISSN 1751-8628 Received on 28th July 2014 Accepted
More informationPERFORMANCE OF TWO-PATH SUCCESSIVE RELAYING IN THE PRESENCE OF INTER-RELAY INTERFERENCE
PERFORMANCE OF TWO-PATH SUCCESSIVE RELAYING IN THE PRESENCE OF INTER-RELAY INTERFERENCE 1 QIAN YU LIAU, 2 CHEE YEN LEOW Wireless Communication Centre, Faculty of Electrical Engineering, Universiti Teknologi
More informationDegrees of Freedom in Multiuser MIMO
Degrees of Freedom in Multiuser MIMO Syed A Jafar Electrical Engineering and Computer Science University of California Irvine, California, 92697-2625 Email: syed@eceuciedu Maralle J Fakhereddin Department
More informationLecture 8 Multi- User MIMO
Lecture 8 Multi- User MIMO I-Hsiang Wang ihwang@ntu.edu.tw 5/7, 014 Multi- User MIMO System So far we discussed how multiple antennas increase the capacity and reliability in point-to-point channels Question:
More informationDegrees of Freedom of MIMO Cellular Networks with Two Cells and Two Users Per Cell
Degrees of Freedom of IO Cellular etworks with Two Cells and Two Users Per Cell Gokul Sridharan and Wei Yu The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto,
More informationBANDWIDTH-PERFORMANCE TRADEOFFS FOR A TRANSMISSION WITH CONCURRENT SIGNALS
BANDWIDTH-PERFORMANCE TRADEOFFS FOR A TRANSMISSION WITH CONCURRENT SIGNALS Aminata A. Garba Dept. of Electrical and Computer Engineering, Carnegie Mellon University aminata@ece.cmu.edu ABSTRACT We consider
More informationMulticast Mode Selection for Multi-antenna Coded Caching
Multicast Mode Selection for Multi-antenna Coded Caching Antti Tölli, Seyed Pooya Shariatpanahi, Jarkko Kaleva and Babak Khalaj Centre for Wireless Communications, University of Oulu, P.O. Box 4500, 9004,
More informationAn Orthogonal Relay Protocol with Improved Diversity-Multiplexing Tradeoff
SUBMITTED TO IEEE TRANS. WIRELESS COMMNS., NOV. 2009 1 An Orthogonal Relay Protocol with Improved Diversity-Multiplexing Tradeoff K. V. Srinivas, Raviraj Adve Abstract Cooperative relaying helps improve
More informationInterference Alignment for Heterogeneous Full-duplex Cellular Networks
Interference Alignment for Heterogeneous ull-duplex Cellular Networks Amr El-Keyi and Halim Yanikomeroglu Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada. Email:
More informationIndex Terms Deterministic channel model, Gaussian interference channel, successive decoding, sum-rate maximization.
3798 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 58, NO 6, JUNE 2012 On the Maximum Achievable Sum-Rate With Successive Decoding in Interference Channels Yue Zhao, Member, IEEE, Chee Wei Tan, Member,
More informationMIMO Interference Management Using Precoding Design
MIMO Interference Management Using Precoding Design Martin Crew 1, Osama Gamal Hassan 2 and Mohammed Juned Ahmed 3 1 University of Cape Town, South Africa martincrew@topmail.co.za 2 Cairo University, Egypt
More informationChapter 10. User Cooperative Communications
Chapter 10 User Cooperative Communications 1 Outline Introduction Relay Channels User-Cooperation in Wireless Networks Multi-Hop Relay Channel Summary 2 Introduction User cooperative communication is a
More informationOn the Capacity Region of the Vector Fading Broadcast Channel with no CSIT
On the Capacity Region of the Vector Fading Broadcast Channel with no CSIT Syed Ali Jafar University of California Irvine Irvine, CA 92697-2625 Email: syed@uciedu Andrea Goldsmith Stanford University Stanford,
More informationOn the Performance of Relay Stations with Multiple Antennas in the Two-Way Relay Channel
EUROPEAN COOPERATION IN THE FIELD OF SCIENTIFIC AND TECHNICAL RESEARCH EURO-COST SOURCE: Technische Universität Darmstadt Institute of Telecommunications Communications Engineering Lab COST 2100 TD(07)
More informationDegrees of Freedom Region for the MIMO X Channel
Degrees of Freedom Region for the MIMO X Channel Syed A. Jafar Electrical Engineering and Computer Science University of California Irvine, Irvine, California, 9697, USA Email: syed@uci.edu Shlomo Shamai
More informationInformation-Theoretic Study on Routing Path Selection in Two-Way Relay Networks
Information-Theoretic Study on Routing Path Selection in Two-Way Relay Networks Shanshan Wu, Wenguang Mao, and Xudong Wang UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China Email:
More informationISSN Vol.03,Issue.17 August-2014, Pages:
www.semargroup.org, www.ijsetr.com ISSN 2319-8885 Vol.03,Issue.17 August-2014, Pages:3542-3548 Implementation of MIMO Multi-Cell Broadcast Channels Based on Interference Alignment Techniques B.SANTHOSHA
More informationBounds on Achievable Rates for Cooperative Channel Coding
Bounds on Achievable Rates for Cooperative Channel Coding Ameesh Pandya and Greg Pottie Department of Electrical Engineering University of California, Los Angeles {ameesh, pottie}@ee.ucla.edu Abstract
More informationStability Regions of Two-Way Relaying with Network Coding
Stability Regions of Two-Way Relaying with Network Coding (Invited Paper) Ertugrul Necdet Ciftcioglu Department of Electrical Engineering The Pennsylvania State University University Park, PA 680 enc8@psu.edu
More informationPerformance Enhancement of Interference Alignment Techniques for MIMO Multi Cell Networks
Performance Enhancement of Interference Alignment Techniques for MIMO Multi Cell Networks B.Vijayanarasimha Raju 1 PG Student, ECE Department Gokula Krishna College of Engineering Sullurpet, India e-mail:
More information3432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 53, NO. 10, OCTOBER 2007
3432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 53, NO 10, OCTOBER 2007 Resource Allocation for Wireless Fading Relay Channels: Max-Min Solution Yingbin Liang, Member, IEEE, Venugopal V Veeravalli, Fellow,
More informationOPTIMAL POWER ALLOCATION FOR MULTIPLE ACCESS CHANNEL
International Journal of Wireless & Mobile Networks (IJWMN) Vol. 8, No. 6, December 06 OPTIMAL POWER ALLOCATION FOR MULTIPLE ACCESS CHANNEL Zouhair Al-qudah Communication Engineering Department, AL-Hussein
More informationState-Dependent Relay Channel: Achievable Rate and Capacity of a Semideterministic Class
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 59, NO. 5, MAY 2013 2629 State-Dependent Relay Channel: Achievable Rate and Capacity of a Semideterministic Class Majid Nasiri Khormuji, Member, IEEE, Abbas
More informationA Bit of network information theory
Š#/,% 0/,94%#(.)15% A Bit of network information theory Suhas Diggavi 1 Email: suhas.diggavi@epfl.ch URL: http://licos.epfl.ch Parts of talk are joint work with S. Avestimehr 2, S. Mohajer 1, C. Tian 3,
More informationOn the Optimum Power Allocation in the One-Side Interference Channel with Relay
2012 IEEE Wireless Communications and etworking Conference: Mobile and Wireless etworks On the Optimum Power Allocation in the One-Side Interference Channel with Relay Song Zhao, Zhimin Zeng, Tiankui Zhang
More informationKURSOR Menuju Solusi Teknologi Informasi Vol. 9, No. 1, Juli 2017
Jurnal Ilmiah KURSOR Menuju Solusi Teknologi Informasi Vol. 9, No. 1, Juli 2017 ISSN 0216 0544 e-issn 2301 6914 OPTIMAL RELAY DESIGN OF ZERO FORCING EQUALIZATION FOR MIMO MULTI WIRELESS RELAYING NETWORKS
More informationReflections on the Capacity Region of the Multi-Antenna Broadcast Channel Hanan Weingarten
IEEE IT SOCIETY NEWSLETTER 1 Reflections on the Capacity Region of the Multi-Antenna Broadcast Channel Hanan Weingarten Yossef Steinberg Shlomo Shamai (Shitz) whanan@tx.technion.ac.ilysteinbe@ee.technion.ac.il
More informationPerformance Analysis of Multiuser MIMO Systems with Scheduling and Antenna Selection
Performance Analysis of Multiuser MIMO Systems with Scheduling and Antenna Selection Mohammad Torabi Wessam Ajib David Haccoun Dept. of Electrical Engineering Dept. of Computer Science Dept. of Electrical
More informationIN RECENT years, wireless multiple-input multiple-output
1936 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 3, NO. 6, NOVEMBER 2004 On Strategies of Multiuser MIMO Transmit Signal Processing Ruly Lai-U Choi, Michel T. Ivrlač, Ross D. Murch, and Wolfgang
More informationCooperative Tx/Rx Caching in Interference Channels: A Storage-Latency Tradeoff Study
Cooperative Tx/Rx Caching in Interference Channels: A Storage-Latency Tradeoff Study Fan Xu Kangqi Liu and Meixia Tao Dept of Electronic Engineering Shanghai Jiao Tong University Shanghai China Emails:
More informationOn Achieving Local View Capacity Via Maximal Independent Graph Scheduling
On Achieving Local View Capacity Via Maximal Independent Graph Scheduling Vaneet Aggarwal, A. Salman Avestimehr and Ashutosh Sabharwal Abstract If we know more, we can achieve more. This adage also applies
More informationCapacity-Achieving Rateless Polar Codes
Capacity-Achieving Rateless Polar Codes arxiv:1508.03112v1 [cs.it] 13 Aug 2015 Bin Li, David Tse, Kai Chen, and Hui Shen August 14, 2015 Abstract A rateless coding scheme transmits incrementally more and
More informationPower Allocation for Three-Phase Two-Way Relay Networks with Simultaneous Wireless Information and Power Transfer
Power Allocation for Three-Phase Two-Way Relay Networks with Simultaneous Wireless Information and Power Transfer Shahab Farazi and D. Richard Brown III Worcester Polytechnic Institute 100 Institute Rd,
More informationOn Fading Broadcast Channels with Partial Channel State Information at the Transmitter
On Fading Broadcast Channels with Partial Channel State Information at the Transmitter Ravi Tandon 1, ohammad Ali addah-ali, Antonia Tulino, H. Vincent Poor 1, and Shlomo Shamai 3 1 Dept. of Electrical
More informationIN MOST situations, the wireless channel suffers attenuation
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 17, NO. 3, MARCH 1999 451 Space Time Block Coding for Wireless Communications: Performance Results Vahid Tarokh, Member, IEEE, Hamid Jafarkhani, Member,
More informationTHE emergence of multiuser transmission techniques for
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 54, NO. 10, OCTOBER 2006 1747 Degrees of Freedom in Wireless Multiuser Spatial Multiplex Systems With Multiple Antennas Wei Yu, Member, IEEE, and Wonjong Rhee,
More informationCOOPERATION via relays that forward information in
4342 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 58, NO. 7, JULY 2012 Relaying in the Presence of Interference: Achievable Rates, Interference Forwarding, and Outer Bounds Ivana Marić, Member, IEEE,
More informationTIME- OPTIMAL CONVERGECAST IN SENSOR NETWORKS WITH MULTIPLE CHANNELS
TIME- OPTIMAL CONVERGECAST IN SENSOR NETWORKS WITH MULTIPLE CHANNELS A Thesis by Masaaki Takahashi Bachelor of Science, Wichita State University, 28 Submitted to the Department of Electrical Engineering
More informationPhysical-Layer Network Coding Using GF(q) Forward Error Correction Codes
Physical-Layer Network Coding Using GF(q) Forward Error Correction Codes Weimin Liu, Rui Yang, and Philip Pietraski InterDigital Communications, LLC. King of Prussia, PA, and Melville, NY, USA Abstract
More informationDiversity Gain Region for MIMO Fading Multiple Access Channels
Diversity Gain Region for MIMO Fading Multiple Access Channels Lihua Weng, Sandeep Pradhan and Achilleas Anastasopoulos Electrical Engineering and Computer Science Dept. University of Michigan, Ann Arbor,
More informationTHE multi-way relay channel [4] is a fundamental building
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 60, NO. 5, MAY 014 495 Degrees of Freedom for the MIMO Multi-Way Relay Channel Ye Tian, Student Member, IEEE, andaylinyener,senior Member, IEEE Abstract This
More informationIMPACT OF SPATIAL CHANNEL CORRELATION ON SUPER QUASI-ORTHOGONAL SPACE-TIME TRELLIS CODES. Biljana Badic, Alexander Linduska, Hans Weinrichter
IMPACT OF SPATIAL CHANNEL CORRELATION ON SUPER QUASI-ORTHOGONAL SPACE-TIME TRELLIS CODES Biljana Badic, Alexander Linduska, Hans Weinrichter Institute for Communications and Radio Frequency Engineering
More informationPAIR-AWARE TRANSCEIVE BEAMFORMING FOR NON-REGENERATIVE MULTI-USER TWO-WAY RELAYING. Aditya Umbu Tana Amah, Anja Klein
A. U. T. Amah and A. Klein, Pair-Aware Transceive Beamforming for Non-Regenerative Multi-User Two-Way Relaying, in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, Dallas,
More informationAnalysis and Improvements of Linear Multi-user user MIMO Precoding Techniques
1 Analysis and Improvements of Linear Multi-user user MIMO Precoding Techniques Bin Song and Martin Haardt Outline 2 Multi-user user MIMO System (main topic in phase I and phase II) critical problem Downlink
More informationProtocol Coding for Two-Way Communications with Half-Duplex Constraints
Protocol Coding for Two-Way Communications with Half-Duplex Constraints Petar Popovski and Osvaldo Simeone Department of Electronic Systems, Aalborg University, Denmark CWCSPR, ECE Dept., NJIT, USA Email:
More informationRouting versus Network Coding in Erasure Networks with Broadcast and Interference Constraints
Routing versus Network Coding in Erasure Networks with Broadcast and Interference Constraints Brian Smith Department of ECE University of Texas at Austin Austin, TX 7872 bsmith@ece.utexas.edu Piyush Gupta
More informationLarge-Scale Multipair Two-Way Relay Networks with Distributed AF Beamforming
Large-Scale ultipair Two-Way Relay Networks with Distributed AF Beamforming Hien Quoc Ngo and Erik G. Larsson Linköping University Post Print N.B.: When citing this work, cite the original article. 03
More informationarxiv: v1 [cs.it] 12 Jan 2011
On the Degree of Freedom for Multi-Source Multi-Destination Wireless Networ with Multi-layer Relays Feng Liu, Chung Chan, Ying Jun (Angela) Zhang Abstract arxiv:0.2288v [cs.it] 2 Jan 20 Degree of freedom
More informationIEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 58, NO. 6, JUNE
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 58, NO 6, JUNE 2012 3787 Degrees of Freedom Region for an Interference Network With General Message Demands Lei Ke, Aditya Ramamoorthy, Member, IEEE, Zhengdao
More information/11/$ IEEE
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE Globecom 0 proceedings. Two-way Amplify-and-Forward MIMO Relay
More informationFOR THE PAST few years, there has been a great amount
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 4, APRIL 2005 549 Transactions Letters On Implementation of Min-Sum Algorithm and Its Modifications for Decoding Low-Density Parity-Check (LDPC) Codes
More informationInterference Mitigation in MIMO Interference Channel via Successive Single-User Soft Decoding
Interference Mitigation in MIMO Interference Channel via Successive Single-User Soft Decoding Jungwon Lee, Hyukjoon Kwon, Inyup Kang Mobile Solutions Lab, Samsung US R&D Center 491 Directors Pl, San Diego,
More informationEnhancing Wireless Information and Power Transfer by Exploiting Multi-Antenna Techniques
IEEE COMMUNICATIONS MAGAZINE, FEATURE TOPIC ON ENERGY HARVESTING COMMUNICATIONS, APRIL 2015. 1 Enhancing Wireless Information and Power Transfer by Exploiting Multi-Antenna Techniques arxiv:1501.02429v1
More informationDiversity and Freedom: A Fundamental Tradeoff in Multiple Antenna Channels
Diversity and Freedom: A Fundamental Tradeoff in Multiple Antenna Channels Lizhong Zheng and David Tse Department of EECS, U.C. Berkeley Feb 26, 2002 MSRI Information Theory Workshop Wireless Fading Channels
More informationTHIS paper addresses the interference channel with a
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 6, NO. 8, AUGUST 07 599 The Degrees of Freedom of the Interference Channel With a Cognitive Relay Under Delayed Feedback Hyo Seung Kang, Student Member, IEEE,
More informationRecovering Multiplexing Loss Through Successive Relaying Using Repetition Coding
SUBMITTED TO IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 1 Recovering Multiplexing Loss Through Successive Relaying Using Repetition Coding Yijia Fan, Chao Wang, John Thompson, H. Vincent Poor arxiv:0705.3261v1
More informationSPACE TIME coding for multiple transmit antennas has attracted
486 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 50, NO. 3, MARCH 2004 An Orthogonal Space Time Coded CPM System With Fast Decoding for Two Transmit Antennas Genyuan Wang Xiang-Gen Xia, Senior Member,
More informationTransmit Power Adaptation for Multiuser OFDM Systems
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 21, NO. 2, FEBRUARY 2003 171 Transmit Power Adaptation Multiuser OFDM Systems Jiho Jang, Student Member, IEEE, Kwang Bok Lee, Member, IEEE Abstract
More informationCommunication over MIMO X Channel: Signalling and Performance Analysis
Communication over MIMO X Channel: Signalling and Performance Analysis Mohammad Ali Maddah-Ali, Abolfazl S. Motahari, and Amir K. Khandani Coding & Signal Transmission Laboratory Department of Electrical
More informationDelay Tolerant Cooperation in the Energy Harvesting Multiple Access Channel
Delay Tolerant Cooperation in the Energy Harvesting Multiple Access Channel Onur Kaya, Nugman Su, Sennur Ulukus, Mutlu Koca Isik University, Istanbul, Turkey, onur.kaya@isikun.edu.tr Bogazici University,
More informationDownlink Performance of Cell Edge User Using Cooperation Scheme in Wireless Cellular Network
Quest Journals Journal of Software Engineering and Simulation Volume1 ~ Issue1 (2013) pp: 07-12 ISSN(Online) :2321-3795 ISSN (Print):2321-3809 www.questjournals.org Research Paper Downlink Performance
More information